Program Description

This master’s course aims to respond to the demand for data scientists with the skills to develop innovative computational intelligence applications, capable of analysing large amounts of complex data to inform businesses decisions and market strategies.

• The main theme throughout this course is automatic big data processing and information retrieval through machine learning, neural network and evolutionary computing.
• We aim to cover how to apply cutting-edge machine learning techniques to analyse big datasets, assess the statistical significance of data mining results and perform advanced data mining tasks.
• We will introduce you to important frameworks which may include Hadoop Map Reduce, Spark, applications of relational databases and NoSQL databases in combination with easy to use and powerful development tools such as Python, R and Matlab.
• We will look at emerging theories, practices, approaches and management of distributed and intelligent computing systems, examining a wide range of case studies to see how applications have been developed and for what purposes, such as steganography detection system for colour stego images.
• The focus of the course is on applications of data science methods and tools, combined with computational intelligence techniques for data-driven problem solving including the analysis, interpretation and visualisation of complex data, which is in increasing demand in fields such as marketing, pharmaceutics, finance, transportation, medicine, and management.
• You will have the option to apply for a ‘work placement’ opportunity, designed to further develop your skills and knowledge with the aim of maximising your employability prospects. 

On successful completion, you will have knowledge of:

• The fundamental principles and techniques of data science and computational intelligence.
• Analysing complex, high-volume, high-dimensional, structured/unstructured data from varying sources.
• The combination of theory and practical application of data science and computational intelligence methods and techniques.
• Professional, legal, social, cultural and ethical issues related to data science, computational intelligence and an awareness of societal and environmental impact.

On successful completion, you will be able to:

• Critically evaluate current research problems and apply cutting-edge developments of data science and to computational intelligence areas.
• Critically evaluate a range of possible options solutions or architectures to address a sizeable data application and present a soundly reasoned justification for the final solution.
• Demonstrate competence, creativity, and innovation in solving unfamiliar problems.
• Effectively communicate outcomes from major projects to technical and non-technical audiences. Select and apply relevant knowledge and skills in big data applications using relevant tools and technologies.
• Identify and make effective and systematic use of a range of suitable techniques for developing solutions to complex data and analytical problems.

Admission Requirements

• Applicants for this programme will normally be expected to possess a minimum of a second class honours degree in Computer science, Mathematics or other relevant discipline.
• General Requirement :-
  • Indian Students-Students must achieve 60% in a 3 Year Undergraduate Degree or 55% in a 4 Year.Undergraduate Degree Students from the following Universities will be considered with 55% in a 3 Year Undergraduate Degree (unless applying for Health and Life Science courses): Delhi, Mumbai, Kolkata, Chennai (Madras), Anna, Amity, Andhra Pradesh, Aligarh Muslim, Pune, Bangalore and JNTU.
  • Arab Students-Students who hold a Bachelor’s Degree should have an average grade of 60% or above. Students who have an average grade of 70% or CGPA of 2.5 out of 4 for the Postgraduate Research programmes with a satisfactory research proposal.

IELTS Requirements

Listening	Reading	Writing	Speaking	Overall
5.5	5.5	5.5	5.5	6

Remarks:

 Indian Students IELTS Waiver:-65% in Standard XII English language from certain examination boards only (Central boards, Maharashtra, West Bengal, Karnataka, Tamil Nadu, Andhra Pradesh, Kerala and Uttarakhand)